Large language models are revolutionizing finance from market analysis to compliance automation but applying them in practice can be challenging. LLMs in Finance is a step-by-step guide that demystifies these powerful models and shows you how to implement them in real financial projects. You'll begin with the fundamentals of how LLMs work, including the transformer architecture, prompt engineering, and fine-tuning for financial data. Next, you'll build applications: intelligent agents for trading; tools for banking tasks like credit scoring and fraud detection; and automated solutions for risk management and regulatory compliance. To deploy these solutions, you'll learn how to scale LLM implementations, from choosing the right hardware to adopting effective cloud strategies. You'll also explore advanced methods to improve model performance, including reinforcement learning for fine-tuning. Finally, learn how to address AI bias and ensure your LLM solutions comply with ethical and regulatory requirements. Real-world case studies illustrate how financial organizations are leveraging LLMs in trading systems, customer service chatbots, and more.
By the end of the book, you'll have the expertise to build LLM-powered applications and pick up on trends such as multimodal AI

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Spis treści

Large Language Models in Finance. A hands-on guide to applying Large Language Models in trading, banking, risk & financial compliance eBook -- spis treści

• 1. Introduction to Large Language Models
• 2. Core Technologies and Implementations
• 3. Financial Agents
• 4. Financial Market Applications
• 5. Banking Applications
• 6. Financial Document Processing and Advisory
• 7. Reinforcement Learning in LLMs
• 8. Infrastructure and Performance
• 9. Ethics, Governance and Compliance
• 10. Future Developments
• 11. Technical Foundations